Car Damage Evaluation

Machine Learning

Evaluating potential damage in a car entails reviewing the car from every angle. However, most data labelling solutions don't have support for multimodal data structures, thereby preventing annotators from getting the full picture.

This template provides users with a 360 degree view of the car to ensure any potential damage is annotated in a cohesive way, while increasing efficiency.

You can edit this layout to expose additional task metadata if you wish, without needing to write any code. Just go to "Edit Workflow", and leverage our rich set of data types to create the right UI for your task's requirements.

Get started with this Template